Distribution Coding in the Visual Pathway

Although a variety of types of spike interval histograms have been reported, little attention has been given to the spike interval distribution as a neural code and to how different distributions are transmitted through neural networks. In this paper we present experimental results showing spike interval histograms recorded from retinal ganglion cells of the cat. These results exhibit a clear correlation between spike interval distribution and stimulus condition at the retinal ganglion cell level. The averaged mean rates of the cells studied were nearly the same in light as in darkness whereas the spike interval histograms were much more regular in light than in darkness. We present theoretical models which illustrate how such a distribution coding at the retinal level could be “interpreted” or recorded at some higher level of the nervous system such as the lateral geniculate nucleus. Interpretation is an essential requirement of a neural code which has often been overlooked in modeling studies. Analytical expressions are derived describing the role of distribution coding in determining the transfer characteristics of a simple interaction model and of a lateral inhibition network. Our work suggests that distribution coding might be interpreted by simply interconnected neural networks such as relay cell networks, in general, and the primary thalamic sensory nuclei in particular